Modelling SO₂ conversion into sulphates in the mid-troposphere with a 3D chemistry-transport model: the case of Mount Etna's eruption on April 12, 2012

Volcanic activity is an important source of atmospheric sulphur dioxide (SO2), which, after conversion into sulphuric acid, induces impacts on, among others, rain acidity, human health, meteorology and the radiative balance of the atmosphere. This work focuses on the conversion of SO2 into sulphates (, S(+VI)) in the mid-tropospheric volcanic plume emitted by the explosive eruption of Mount Etna (Italy) on Apr. 12, 2012, using the CHIMERE chemistry-transport model. Since volcanic plume location and composition depend on several often poorly constrained parameters, using a chemistry-transport model allows us to study the sensitivity of SO2 oxidation to multiple aspects such as volcanic water emissions, transition metal emissions, plume diffusion and plume altitude. Our results show that in the mid-troposphere, two pathways contribute to sulphate production, the oxidation of SO2 by OH in the gaseous phase (70 %), and the aqueous oxidation by O2 catalyzed by Mn2+ and Fe3+ ions (25 %). The oxidation in aqueous phase is the faster process, but in the mid-troposphere, liquid water is scarce, therefore the relative share of gaseous oxidation can be important. After one day in the mid-troposphere, about 0.5 % of the volcanic SO2 was converted to sulphates through the gaseous process. Because of the nonlinear dependency of the kinetics in the aqueous phase to the amount of volcanic water emitted and on the availability of transition metals in the aqueous phase, several experiments have been designed to determine the prominence of different parameters. Our simulations show that during the short time that liquid water remains in the plume, around 0.4 % of sulphates manage to quickly enter the liquid phase. Sensitivity tests regarding the advection scheme have shown that this scheme must be chosen wisely, as dispersion will impact both oxidation pathways explained above.

Black carbon aerosol reductions during COVID-19 confinement quantified by aircraft measurements over Europe

The abrupt reduction in human activities during the first lockdown of the COVID-19 pandemic created unprecedented atmospheric conditions. To quantify the changes in lower tropospheric air pollution, we conducted the BLUESKY aircraft campaign and measured vertical profiles of black carbon (BC) aerosol particles over Western and Southern Europe in May and June 2020. We compared the results to similar measurements of the EMeRGe EU campaign performed in July 2017 and found that the BC mass concentrations (MBC) were reduced by about 47 %. For BC particle number concentrations, we found comparable reductions. Based on EMAC chemistry-transport model simulations, we find differences in meteorological conditions and flight patterns responsible for about 7 % of the reductions in MBC, whereas 40 % can be attributed to reduced anthropogenic emissions. Our results reflect the strong and immediate positive effect of changes in human activities on air quality and the atmospheric role of BC aerosols as a major air pollutant and climate forcing agent in the Anthropocene.

An improved TROPOMI tropospheric NO₂ research product over Europe

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

Nitrogen deposition in the UK at 1 km resolution from 1990 to 2017

An atmospheric chemistry transport model (FRAME) is used here to calculate annual UK N deposition for the years 1990–2017, at a 1 km × 1 km resolution. Reactive nitrogen (N) deposition is a threat that can lead to adverse effects on the environment and human health. In Europe, substantial reductions in N deposition from nitrogen oxide emissions have been achieved in recent decades. This paper quantifies reductions in UK N deposition following the N emissions peak in 1990. In the UK, estimates of N deposition are typically available at a coarse spatial resolution (typically 5 km × 5 km grid resolution), and it is often difficult to compare estimates between years due to methodological changes in emission estimates. Through efforts to reduce emissions of N from industry, traffic, and agriculture, this study predicts that UK N deposition has reduced from 465 kt N in 1990 to 278 kt N in 2017. However, as part of this overall reduction, there are non-uniform changes for wet and dry deposition of reduced N (NHx) and oxidised N (NOy). In 2017, it is estimated 59 % of all N deposition is in the form of reduced N, a change from 35 % in 1990. This dataset uses 28 years of emissions data from 1990 to 2017 to produce the first long-term dataset of 28 years of N deposition at 1 km × 1 km resolution in the UK. Full data are available at https://doi.org/10.5285/9b203324-6b37-4e91-b028-e073b197fb9f (Tomlinson et al., 2020).

Ozone pollution during the COVID-19 lockdown in the spring 2020 over Europe analysed from satellite observations, in situ measurements and models

We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements and chemistry transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 multispectral synergism, which provides particularly enhanced sensitivity to near-surface ozone pollution. These observations are first analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in Central Europe and Northern Italy, and some other hotspots, which are typically characterized by VOC-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb and the same standard deviation and range of variability). An average bias of ∼8 ppb between the two observational datasets is remarked, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for withdrawing the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry transport model simulations using the meteorological fields of each year and identical emission inventories. This observational estimate of the influence of lockdown emission reduction is consistent for both datasets. They both show lockdown-associated ozone enhancements in hotspots over Central Europe and Northern Italy, with a reduced amplitude with respect to the total changes observed between the two years, and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally highlight the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozonesondes measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry transport model. For analysing the uncertainty of the model estimates, we perform two sets of simulations with different setups, differing in the emission inventories, their modifications to account for changes in anthropogenic activities during the lockdown and the meteorological fields. Whereas a general qualitative consistency of positive and negative ozone anomalies is remarked between all model and observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational data sets, both for enhancements and decreases of ozone, while the large-scale ozone decrease is not simulated. With one of the setups, the model simulates ozone enhancements a factor 3 to 6 smaller than with the other configuration. This is partly linked to the emission inventories of ozone precursors (at least a 30 % difference), but mainly to differences in vertical mixing of atmospheric constituents depending on the choice of the meteorological model.

Refinement of land use data for emission calculations in the CHIMERE chemistry-transport model: A case study for the Nizhny Novgorod region .

Refinement of land use data for emission calculations in the CHIMERE chemistry-transport model: A case study for the Nizhny Novgorod region / Borisov D.V., Shalygina I.U. // Hydrometeorological Research and Forecasting, 2021, no. 3 (381), pp. 150-161. The quality of calculating the concentration of pollutants in the chemistry-transport model largely depends on the reliability of used emission data. The possibility of updating the EMEP (European Monitoring and Evaluation Program) emission data using OpenStreetMap geodata for the CHIMERE chemistry-transport model calculations is discussed on the example of the Nizhny Novgorod region. The GlobCover land-use data refinement procedure based on OpenStreetMap information provides a 3.3% increase in the urban area and a more accurate configuration of the emission field as compared to the real distribution of sources of atmospheric emissions. Experimental CHIMERE chemistry-transport model calculations of pollutant concentrations based on the initial and updated emission fields demonstrated the efficiency of the proposed approach. Keywords: emissions, EMEP, land use, OpenStreetMap, CHIMERE chemistry-transport model, air quality